{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "9e631c99",
   "metadata": {},
   "source": [
    "Script 10-1: Creating course data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "07c0be3f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#import needed packages\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "32d49d64",
   "metadata": {},
   "outputs": [],
   "source": [
    "#create conditional courses that relate to final exam passage rates\n",
    "\n",
    "#course 1, with low passage rates in general\n",
    "course1=np.random.binomial(1,0.75,500)\n",
    "\n",
    "#course 2, with low passage rates on the first attempt if course 1 was failed\n",
    "course2a=np.random.binomial(1,0.95,500)\n",
    "course2b=np.random.binomial(1,0.5,500)\n",
    "course2=np.where(course1>0,course2a,course2b)\n",
    "\n",
    "#course 3, with passage rates relative dependent on prior performance\n",
    "course3a=np.random.binomial(1,0.95,500)\n",
    "course3b=np.random.binomial(1,0.65,500)\n",
    "course3=np.where(course2+course1>1,course3a,course3b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0a5ef774",
   "metadata": {},
   "outputs": [],
   "source": [
    "#create two other courses that are not related to performance on final exam\n",
    "course4=np.random.binomial(1,0.8,200)\n",
    "course5=np.random.binomial(1,0.85,200)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f3733251",
   "metadata": {},
   "outputs": [],
   "source": [
    "#create final exam passage rates\n",
    "passa=np.random.binomial(1,0.95,200)\n",
    "passb=np.random.binomial(1,0.75,200)\n",
    "pass_final=np.where(course1+course2+course3>2,course3a,course3b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "92aeeb0e",
   "metadata": {},
   "outputs": [],
   "source": [
    "Course_Data=pd.DataFrame([course1,course2,course3,course4,course5,pass_final],\n",
    "                        index=['Course_1','Course_2','Course_3','Course_4',\n",
    "                              'Course_5','Pass_Final_Exam']).transpose()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c34e4674",
   "metadata": {},
   "source": [
    "Script 10-2: Create a Bayesian Network"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef708110",
   "metadata": {},
   "outputs": [],
   "source": [
    "#install bnlearn package if not already in directory and import\n",
    "!pip install -U bnlearn\n",
    "import bnlearn as bn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "672cc068",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[bnlearn] >Computing best DAG using [hc]\n",
      "[bnlearn] >Set scoring type at [bic]\n",
      "[bnlearn] >Compute structure scores for model comparison (higher is better).\n"
     ]
    }
   ],
   "source": [
    "#fit Bayesian network\n",
    "model = bn.structure_learning.fit(Course_Data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "46f922b8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "target           Course_1  Course_2  Course_3  Course_4  Course_5  \\\n",
      "source                                                              \n",
      "Course_1            False     False     False     False     False   \n",
      "Course_2             True     False     False     False     False   \n",
      "Course_3            False     False     False     False     False   \n",
      "Course_4            False     False     False     False     False   \n",
      "Course_5            False     False     False     False     False   \n",
      "Pass_Final_Exam      True      True      True     False     False   \n",
      "\n",
      "target           Pass_Final_Exam  \n",
      "source                            \n",
      "Course_1                   False  \n",
      "Course_2                   False  \n",
      "Course_3                   False  \n",
      "Course_4                   False  \n",
      "Course_5                   False  \n",
      "Pass_Final_Exam            False  \n"
     ]
    }
   ],
   "source": [
    "#print dependencies\n",
    "print(model['adjmat'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a76abf82",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[bnlearn] >Set node properties.\n",
      "[bnlearn] >Set edge properties.\n",
      "[bnlearn] >Plot based on Bayesian model\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1500x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "{'fig': <Figure size 1500x1000 with 1 Axes>,\n",
       " 'ax': <Figure size 1500x1000 with 1 Axes>,\n",
       " 'pos': {'Course_1': array([-0.61507226,  0.50218117]),\n",
       "  'Course_2': array([-0.33545472,  0.33425443]),\n",
       "  'Course_3': array([0.67786206, 0.31726667]),\n",
       "  'Course_4': array([ 0.68381937, -0.54626803]),\n",
       "  'Course_5': array([-0.40250751, -1.        ]),\n",
       "  'Pass_Final_Exam': array([-0.00864696,  0.39256575])},\n",
       " 'G': <networkx.classes.digraph.DiGraph at 0x1b58b62e790>,\n",
       " 'node_properties': {'Course_1': {'node_color': '#1f456e', 'node_size': 800},\n",
       "  'Course_2': {'node_color': '#1f456e', 'node_size': 800},\n",
       "  'Course_3': {'node_color': '#1f456e', 'node_size': 800},\n",
       "  'Course_4': {'node_color': '#1f456e', 'node_size': 800},\n",
       "  'Course_5': {'node_color': '#1f456e', 'node_size': 800},\n",
       "  'Pass_Final_Exam': {'node_color': '#1f456e', 'node_size': 800}},\n",
       " 'edge_properties': {('Course_2', 'Course_1'): {'color': '#000000',\n",
       "   'weight': 1},\n",
       "  ('Pass_Final_Exam', 'Course_1'): {'color': '#000000', 'weight': 1},\n",
       "  ('Pass_Final_Exam', 'Course_2'): {'color': '#000000', 'weight': 1},\n",
       "  ('Pass_Final_Exam', 'Course_3'): {'color': '#000000', 'weight': 1}}}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#plot Bayesian network derived from dataset\n",
    "bn.plot(model)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e74f4a83",
   "metadata": {},
   "source": [
    "Script 10-3: A second Bayesian network with different fitting algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f605bf97",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[bnlearn] >Computing best DAG using [ex]\n",
      "[bnlearn] >Set scoring type at [bic]\n",
      "[bnlearn] >Compute structure scores for model comparison (higher is better).\n"
     ]
    }
   ],
   "source": [
    "#fit Bayesian network\n",
    "model = bn.structure_learning.fit(Course_Data.iloc[:,0:3], methodtype='ex')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b7c2421e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "target    Course_1  Course_2  Course_3\n",
      "source                                \n",
      "Course_1     False      True      True\n",
      "Course_2     False     False      True\n",
      "Course_3     False     False     False\n"
     ]
    }
   ],
   "source": [
    "#print dependencies\n",
    "print(model['adjmat'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "dd25f6ea",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[bnlearn] >Set node properties.\n",
      "[bnlearn] >Set edge properties.\n",
      "[bnlearn] >Plot based on Bayesian model\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1500x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "{'fig': <Figure size 1500x1000 with 1 Axes>,\n",
       " 'ax': <Figure size 1500x1000 with 1 Axes>,\n",
       " 'pos': {'Course_1': array([-0.41115324,  0.19992096]),\n",
       "  'Course_2': array([0.58209633, 0.80007904]),\n",
       "  'Course_3': array([-0.17094309, -1.        ])},\n",
       " 'G': <networkx.classes.digraph.DiGraph at 0x1b58e88dbe0>,\n",
       " 'node_properties': {'Course_1': {'node_color': '#1f456e', 'node_size': 800},\n",
       "  'Course_2': {'node_color': '#1f456e', 'node_size': 800},\n",
       "  'Course_3': {'node_color': '#1f456e', 'node_size': 800}},\n",
       " 'edge_properties': {('Course_1', 'Course_2'): {'color': '#000000',\n",
       "   'weight': 1},\n",
       "  ('Course_1', 'Course_3'): {'color': '#000000', 'weight': 1},\n",
       "  ('Course_2', 'Course_3'): {'color': '#000000', 'weight': 1}}}"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#plot Bayesian network derived from dataset\n",
    "bn.plot(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c3eb92a9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
